The concept of resource pool has a very long history. Propelled by the need to
share CPU cycles of supercomputers for highthroughput computing jobs from the
scientific community, the vision is most recently explored by the advocates of
Grid. On the other hand, the advent of P2P researches has demonstrated the
feasibility of integrating potentially unlimited amount of less powerful machines
around the world. Organizing a P2P resource pool thus becomes an interesting
research topic. This paper attempts to address two problems. The first is how to
organize a P2P resource pool, and our answer is to combine the self-organizing
strength of P2P DHT with an in-system, selfscaling monitoring infrastructure that
is layered on top of DHT. The second question is the utility of the P2P resource
pool for interesting applications. And we choose to showcase its power by
optimizing wide-area application level multicasting (ALM), a problem far more
challenging and interesting than conventional tasks such as massively parallel
computation. We show that utilizing spare resources in the pool results in
significant savings for single ALM session. Furthermore, we adopt a purely
market-driven approach to optimize multiple concurrent sessions. As expected,
sessions of higher priority are given higher share of resources.